An identification apparatus is needed to be installed on a machine for processing financial bills in order to identify characteristics of the processed financial bills. For example, a banknote identification device is provided on a financial device, such as, an automated teller machine (ATM), a sorter, a counting machine, which is mainly used for identifying a currency, a denomination, an orientation and a legitimacy of a banknote. Since some anti-counterfeit marks are added to banknotes in the process of designing and printing the banknotes, the banknote identification apparatus is generally provided with some sensors for detecting and acquiring related anti-counterfeit marks. For example, a surface image or a transmission image of banknotes is acquired by irritating the banknotes by light with different wavelengths, and then the banknotes are identified according to the acquired information of relevant images.
At present, the image information acquired by the above-mentioned optical image sensors is stored in a predetermined identification image memory, and then an image identification module identifies a currency, a denomination, an orientation and a legitimacy of a stored image of each valuable document. Since the identification module may fail to identify the acquired image information, in order to analyze and study the reasons for identification failures, the image information failing to be identified (hereinafter referred to as “rejected banknote image”) is stored. According to the stored the rejected banknote image, a developer can conveniently find some faults of the sensor hardware or the identification module or find algorithm defects, so as to provide a basis for further improvement. An existing method for storing a rejected banknote image is shown in FIG. 1, and the image information failing to be identified is copied from an identification image memory to a rejected banknote image memory which is set in advance.
When a single CPU is used, the process of copying the rejected banknote images can not be operated at the same time as the process of identifying images in algorithm, and these processes must be performed in sequence. Therefore, when the identification module fails to identify an image, a lot of time is spent on copying the image to the rejected banknote image memory. Thus, the identification module has to stop the identification on other images, which greatly influences the identification speed of the identification module. In order to meet the requirement of ATM for high speed processing on valuable documents, how to spend the processing time of CPU mostly on identifying the acquired image information and reduce the time wasted on non-identification calculation as much as possible, are the technical problems which those skilled in the art have been trying to solve.